Overview

Brought to you by YData

Dataset statistics

Number of variables14
Number of observations3556
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows41
Duplicate rows (%)1.2%
Total size in memory389.1 KiB
Average record size in memory112.0 B

Variable types

Text9
Categorical4
Numeric1

Alerts

Dataset has 41 (1.2%) duplicate rowsDuplicates
District Name is highly overall correlated with Postal DistrictHigh correlation
Floor Level is highly overall correlated with Property Type and 1 other fieldsHigh correlation
Postal District is highly overall correlated with District NameHigh correlation
Property Type is highly overall correlated with Floor Level and 1 other fieldsHigh correlation
Type of Area is highly overall correlated with Floor Level and 1 other fieldsHigh correlation

Reproduction

Analysis started2024-11-22 10:48:28.074112
Analysis finished2024-11-22 10:48:28.803277
Duration0.73 seconds
Software versionydata-profiling vv4.12.0
Download configurationconfig.json

Variables

Distinct341
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2024-11-22T18:48:29.261493image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length40
Median length28
Mean length15.30793
Min length3

Characters and Unicode

Total characters54435
Distinct characters40
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)3.1%

Sample

1st rowSUNSHINE PLAZA
2nd rowPAYA LEBAR SQUARE
3rd rowWOODS SQUARE
4th rowSUNSHINE PLAZA
5th rowINTERNATIONAL PLAZA
ValueCountFrequency (%)
conservation 438
 
5.2%
area 438
 
5.2%
plaza 409
 
4.8%
n.a 379
 
4.5%
square 359
 
4.2%
the 311
 
3.7%
centre 309
 
3.6%
shopping 221
 
2.6%
india 143
 
1.7%
little 143
 
1.7%
Other values (410) 5320
62.8%
2024-11-22T18:48:29.778299image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 5970
11.0%
E 5478
 
10.1%
4914
 
9.0%
N 4567
 
8.4%
O 3494
 
6.4%
R 3483
 
6.4%
T 3451
 
6.3%
I 3046
 
5.6%
S 2621
 
4.8%
L 2601
 
4.8%
Other values (30) 14810
27.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 48268
88.7%
Space Separator 4914
 
9.0%
Other Punctuation 958
 
1.8%
Decimal Number 290
 
0.5%
Dash Punctuation 5
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 5970
12.4%
E 5478
11.3%
N 4567
 
9.5%
O 3494
 
7.2%
R 3483
 
7.2%
T 3451
 
7.1%
I 3046
 
6.3%
S 2621
 
5.4%
L 2601
 
5.4%
P 1880
 
3.9%
Other values (16) 11677
24.2%
Decimal Number
ValueCountFrequency (%)
1 107
36.9%
2 66
22.8%
0 45
15.5%
5 25
 
8.6%
8 18
 
6.2%
3 14
 
4.8%
9 9
 
3.1%
7 6
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 758
79.1%
@ 122
 
12.7%
' 54
 
5.6%
/ 24
 
2.5%
Space Separator
ValueCountFrequency (%)
4914
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 48268
88.7%
Common 6167
 
11.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 5970
12.4%
E 5478
11.3%
N 4567
 
9.5%
O 3494
 
7.2%
R 3483
 
7.2%
T 3451
 
7.1%
I 3046
 
6.3%
S 2621
 
5.4%
L 2601
 
5.4%
P 1880
 
3.9%
Other values (16) 11677
24.2%
Common
ValueCountFrequency (%)
4914
79.7%
. 758
 
12.3%
@ 122
 
2.0%
1 107
 
1.7%
2 66
 
1.1%
' 54
 
0.9%
0 45
 
0.7%
5 25
 
0.4%
/ 24
 
0.4%
8 18
 
0.3%
Other values (4) 34
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54435
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 5970
11.0%
E 5478
 
10.1%
4914
 
9.0%
N 4567
 
8.4%
O 3494
 
6.4%
R 3483
 
6.4%
T 3451
 
6.3%
I 3046
 
5.6%
S 2621
 
4.8%
L 2601
 
4.8%
Other values (30) 14810
27.2%
Distinct307
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2024-11-22T18:48:30.358345image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length13.906074
Min length9

Characters and Unicode

Total characters49450
Distinct characters41
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)2.7%

Sample

1st rowBENCOOLEN STREET
2nd rowPAYA LEBAR ROAD
3rd rowWOODLANDS SQUARE
4th rowBENCOOLEN STREET
5th rowANSON ROAD
ValueCountFrequency (%)
road 2205
25.9%
street 569
 
6.7%
jalan 213
 
2.5%
bridge 193
 
2.3%
upper 189
 
2.2%
north 143
 
1.7%
serangoon 134
 
1.6%
geylang 126
 
1.5%
cecil 115
 
1.3%
paya 114
 
1.3%
Other values (346) 4519
53.0%
2024-11-22T18:48:30.825953image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 5857
11.8%
R 5108
10.3%
4964
10.0%
O 4722
9.5%
E 4640
9.4%
D 3244
 
6.6%
N 2925
 
5.9%
T 2631
 
5.3%
S 2357
 
4.8%
L 1702
 
3.4%
Other values (31) 11300
22.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 44394
89.8%
Space Separator 4964
 
10.0%
Decimal Number 77
 
0.2%
Other Punctuation 10
 
< 0.1%
Dash Punctuation 5
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 5857
13.2%
R 5108
11.5%
O 4722
10.6%
E 4640
10.5%
D 3244
 
7.3%
N 2925
 
6.6%
T 2631
 
5.9%
S 2357
 
5.3%
L 1702
 
3.8%
I 1601
 
3.6%
Other values (16) 9607
21.6%
Decimal Number
ValueCountFrequency (%)
1 23
29.9%
9 15
19.5%
3 10
13.0%
7 8
 
10.4%
2 8
 
10.4%
5 5
 
6.5%
6 4
 
5.2%
8 2
 
2.6%
4 2
 
2.6%
Other Punctuation
ValueCountFrequency (%)
' 4
40.0%
. 3
30.0%
/ 2
20.0%
\ 1
 
10.0%
Space Separator
ValueCountFrequency (%)
4964
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 44394
89.8%
Common 5056
 
10.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 5857
13.2%
R 5108
11.5%
O 4722
10.6%
E 4640
10.5%
D 3244
 
7.3%
N 2925
 
6.6%
T 2631
 
5.9%
S 2357
 
5.3%
L 1702
 
3.8%
I 1601
 
3.6%
Other values (16) 9607
21.6%
Common
ValueCountFrequency (%)
4964
98.2%
1 23
 
0.5%
9 15
 
0.3%
3 10
 
0.2%
7 8
 
0.2%
2 8
 
0.2%
- 5
 
0.1%
5 5
 
0.1%
6 4
 
0.1%
' 4
 
0.1%
Other values (5) 10
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49450
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 5857
11.8%
R 5108
10.3%
4964
10.0%
O 4722
9.5%
E 4640
9.4%
D 3244
 
6.6%
N 2925
 
5.9%
T 2631
 
5.3%
S 2357
 
4.8%
L 1702
 
3.4%
Other values (31) 11300
22.9%

Property Type
Categorical

High correlation 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
Office
1532 
Retail
1221 
Shop House
803 

Length

Max length10
Median length6
Mean length6.9032621
Min length6

Characters and Unicode

Total characters24548
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOffice
2nd rowOffice
3rd rowOffice
4th rowOffice
5th rowOffice

Common Values

ValueCountFrequency (%)
Office 1532
43.1%
Retail 1221
34.3%
Shop House 803
22.6%

Length

2024-11-22T18:48:30.886457image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-22T18:48:30.932406image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
office 1532
35.1%
retail 1221
28.0%
shop 803
18.4%
house 803
18.4%

Most occurring characters

ValueCountFrequency (%)
e 3556
14.5%
f 3064
12.5%
i 2753
11.2%
o 1606
 
6.5%
O 1532
 
6.2%
c 1532
 
6.2%
a 1221
 
5.0%
l 1221
 
5.0%
t 1221
 
5.0%
R 1221
 
5.0%
Other values (7) 5621
22.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 19386
79.0%
Uppercase Letter 4359
 
17.8%
Space Separator 803
 
3.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3556
18.3%
f 3064
15.8%
i 2753
14.2%
o 1606
8.3%
c 1532
7.9%
a 1221
 
6.3%
l 1221
 
6.3%
t 1221
 
6.3%
h 803
 
4.1%
p 803
 
4.1%
Other values (2) 1606
8.3%
Uppercase Letter
ValueCountFrequency (%)
O 1532
35.1%
R 1221
28.0%
S 803
18.4%
H 803
18.4%
Space Separator
ValueCountFrequency (%)
803
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23745
96.7%
Common 803
 
3.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3556
15.0%
f 3064
12.9%
i 2753
11.6%
o 1606
 
6.8%
O 1532
 
6.5%
c 1532
 
6.5%
a 1221
 
5.1%
l 1221
 
5.1%
t 1221
 
5.1%
R 1221
 
5.1%
Other values (6) 4818
20.3%
Common
ValueCountFrequency (%)
803
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24548
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 3556
14.5%
f 3064
12.5%
i 2753
11.2%
o 1606
 
6.5%
O 1532
 
6.2%
c 1532
 
6.2%
a 1221
 
5.0%
l 1221
 
5.0%
t 1221
 
5.0%
R 1221
 
5.0%
Other values (7) 5621
22.9%
Distinct1670
Distinct (%)47.0%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2024-11-22T18:48:31.631930image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length8.5672103
Min length7

Characters and Unicode

Total characters30465
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1199 ?
Unique (%)33.7%

Sample

1st row850,000
2nd row2,318,000
3rd row1,230,000
4th row1,120,000
5th row1,763,580
ValueCountFrequency (%)
3,500,000 25
 
0.7%
1,200,000 25
 
0.7%
1,500,000 24
 
0.7%
1,300,000 23
 
0.6%
900,000 22
 
0.6%
2,000,000 22
 
0.6%
950,000 21
 
0.6%
700,000 21
 
0.6%
1,800,000 21
 
0.6%
1,100,000 20
 
0.6%
Other values (1660) 3332
93.7%
2024-11-22T18:48:32.293137image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13350
43.8%
, 6155
20.2%
1 1891
 
6.2%
8 1635
 
5.4%
5 1538
 
5.0%
2 1389
 
4.6%
3 1173
 
3.9%
6 974
 
3.2%
4 897
 
2.9%
7 766
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24310
79.8%
Other Punctuation 6155
 
20.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13350
54.9%
1 1891
 
7.8%
8 1635
 
6.7%
5 1538
 
6.3%
2 1389
 
5.7%
3 1173
 
4.8%
6 974
 
4.0%
4 897
 
3.7%
7 766
 
3.2%
9 697
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 6155
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30465
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13350
43.8%
, 6155
20.2%
1 1891
 
6.2%
8 1635
 
5.4%
5 1538
 
5.0%
2 1389
 
4.6%
3 1173
 
3.9%
6 974
 
3.2%
4 897
 
2.9%
7 766
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30465
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13350
43.8%
, 6155
20.2%
1 1891
 
6.2%
8 1635
 
5.4%
5 1538
 
5.0%
2 1389
 
4.6%
3 1173
 
3.9%
6 974
 
3.2%
4 897
 
2.9%
7 766
 
2.5%
Distinct904
Distinct (%)25.4%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2024-11-22T18:48:32.858798image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length10
Median length6
Mean length6.7260967
Min length3

Characters and Unicode

Total characters23918
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique549 ?
Unique (%)15.4%

Sample

1st row484.38
2nd row1,065.64
3rd row559.73
4th row635.08
5th row968.76
ValueCountFrequency (%)
344.45 61
 
1.7%
398.27 58
 
1.6%
559.73 58
 
1.6%
635.08 43
 
1.2%
645.84 42
 
1.2%
516.67 41
 
1.2%
204.52 41
 
1.2%
505.91 40
 
1.1%
441.32 40
 
1.1%
484.38 40
 
1.1%
Other values (894) 3092
87.0%
2024-11-22T18:48:33.431918image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3541
14.8%
1 2650
11.1%
2 2127
8.9%
3 2081
8.7%
4 1999
8.4%
5 1999
8.4%
6 1823
7.6%
8 1711
7.2%
9 1642
6.9%
7 1599
6.7%
Other values (2) 2746
11.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18984
79.4%
Other Punctuation 4934
 
20.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2650
14.0%
2 2127
11.2%
3 2081
11.0%
4 1999
10.5%
5 1999
10.5%
6 1823
9.6%
8 1711
9.0%
9 1642
8.6%
7 1599
8.4%
0 1353
7.1%
Other Punctuation
ValueCountFrequency (%)
. 3541
71.8%
, 1393
 
28.2%

Most occurring scripts

ValueCountFrequency (%)
Common 23918
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 3541
14.8%
1 2650
11.1%
2 2127
8.9%
3 2081
8.7%
4 1999
8.4%
5 1999
8.4%
6 1823
7.6%
8 1711
7.2%
9 1642
6.9%
7 1599
6.7%
Other values (2) 2746
11.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23918
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3541
14.8%
1 2650
11.1%
2 2127
8.9%
3 2081
8.7%
4 1999
8.4%
5 1999
8.4%
6 1823
7.6%
8 1711
7.2%
9 1642
6.9%
7 1599
6.7%
Other values (2) 2746
11.5%
Distinct2230
Distinct (%)62.7%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2024-11-22T18:48:34.151426image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.9924072
Min length3

Characters and Unicode

Total characters17753
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1475 ?
Unique (%)41.5%

Sample

1st row1,755
2nd row2,175
3rd row2,197
4th row1,764
5th row1,820
ValueCountFrequency (%)
1,858 22
 
0.6%
2,323 20
 
0.6%
2,787 10
 
0.3%
1,800 10
 
0.3%
4,645 10
 
0.3%
2,477 10
 
0.3%
1,394 9
 
0.3%
1,000 9
 
0.3%
2,150 8
 
0.2%
2,230 8
 
0.2%
Other values (2220) 3440
96.7%
2024-11-22T18:48:34.860394image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 3500
19.7%
2 2274
12.8%
1 2044
11.5%
3 1647
9.3%
0 1358
 
7.6%
4 1319
 
7.4%
5 1282
 
7.2%
6 1121
 
6.3%
8 1082
 
6.1%
9 1069
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14253
80.3%
Other Punctuation 3500
 
19.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2274
16.0%
1 2044
14.3%
3 1647
11.6%
0 1358
9.5%
4 1319
9.3%
5 1282
9.0%
6 1121
7.9%
8 1082
7.6%
9 1069
7.5%
7 1057
7.4%
Other Punctuation
ValueCountFrequency (%)
, 3500
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17753
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 3500
19.7%
2 2274
12.8%
1 2044
11.5%
3 1647
9.3%
0 1358
 
7.6%
4 1319
 
7.4%
5 1282
 
7.2%
6 1121
 
6.3%
8 1082
 
6.1%
9 1069
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17753
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 3500
19.7%
2 2274
12.8%
1 2044
11.5%
3 1647
9.3%
0 1358
 
7.6%
4 1319
 
7.4%
5 1282
 
7.2%
6 1121
 
6.3%
8 1082
 
6.1%
9 1069
 
6.0%
Distinct61
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2024-11-22T18:48:35.256554image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters21336
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOct-24
2nd rowOct-24
3rd rowOct-24
4th rowOct-24
5th rowOct-24
ValueCountFrequency (%)
oct-21 95
 
2.7%
jun-22 89
 
2.5%
mar-21 86
 
2.4%
jul-21 86
 
2.4%
jun-23 86
 
2.4%
jun-21 85
 
2.4%
dec-21 85
 
2.4%
apr-21 83
 
2.3%
apr-22 82
 
2.3%
aug-23 79
 
2.2%
Other values (51) 2700
75.9%
2024-11-22T18:48:35.684690image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 4165
19.5%
- 3556
16.7%
1 1056
 
4.9%
u 907
 
4.3%
J 891
 
4.2%
a 863
 
4.0%
e 812
 
3.8%
3 724
 
3.4%
c 664
 
3.1%
r 646
 
3.0%
Other values (19) 7052
33.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7112
33.3%
Lowercase Letter 7112
33.3%
Dash Punctuation 3556
16.7%
Uppercase Letter 3556
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 907
12.8%
a 863
12.1%
e 812
11.4%
c 664
9.3%
r 646
9.1%
n 591
8.3%
p 581
8.2%
t 358
 
5.0%
l 300
 
4.2%
o 299
 
4.2%
Other values (4) 1091
15.3%
Uppercase Letter
ValueCountFrequency (%)
J 891
25.1%
M 603
17.0%
A 593
16.7%
O 358
10.1%
D 306
 
8.6%
N 299
 
8.4%
S 264
 
7.4%
F 242
 
6.8%
Decimal Number
ValueCountFrequency (%)
2 4165
58.6%
1 1056
 
14.8%
3 724
 
10.2%
0 509
 
7.2%
4 498
 
7.0%
9 160
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 3556
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10668
50.0%
Latin 10668
50.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
u 907
 
8.5%
J 891
 
8.4%
a 863
 
8.1%
e 812
 
7.6%
c 664
 
6.2%
r 646
 
6.1%
M 603
 
5.7%
A 593
 
5.6%
n 591
 
5.5%
p 581
 
5.4%
Other values (12) 3517
33.0%
Common
ValueCountFrequency (%)
2 4165
39.0%
- 3556
33.3%
1 1056
 
9.9%
3 724
 
6.8%
0 509
 
4.8%
4 498
 
4.7%
9 160
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21336
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 4165
19.5%
- 3556
16.7%
1 1056
 
4.9%
u 907
 
4.3%
J 891
 
4.2%
a 863
 
4.0%
e 812
 
3.8%
3 724
 
3.4%
c 664
 
3.1%
r 646
 
3.0%
Other values (19) 7052
33.1%

Type of Area
Categorical

High correlation 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
Strata
2761 
Land
795 

Length

Max length6
Median length6
Mean length5.5528684
Min length4

Characters and Unicode

Total characters19746
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowStrata
2nd rowStrata
3rd rowStrata
4th rowStrata
5th rowStrata

Common Values

ValueCountFrequency (%)
Strata 2761
77.6%
Land 795
 
22.4%

Length

2024-11-22T18:48:35.745796image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-22T18:48:35.785555image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
strata 2761
77.6%
land 795
 
22.4%

Most occurring characters

ValueCountFrequency (%)
a 6317
32.0%
t 5522
28.0%
S 2761
14.0%
r 2761
14.0%
L 795
 
4.0%
n 795
 
4.0%
d 795
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16190
82.0%
Uppercase Letter 3556
 
18.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 6317
39.0%
t 5522
34.1%
r 2761
17.1%
n 795
 
4.9%
d 795
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
S 2761
77.6%
L 795
 
22.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 19746
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 6317
32.0%
t 5522
28.0%
S 2761
14.0%
r 2761
14.0%
L 795
 
4.0%
n 795
 
4.0%
d 795
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19746
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 6317
32.0%
t 5522
28.0%
S 2761
14.0%
r 2761
14.0%
L 795
 
4.0%
n 795
 
4.0%
d 795
 
4.0%
Distinct904
Distinct (%)25.4%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2024-11-22T18:48:36.134916image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length9
Median length2
Mean length2.8082115
Min length1

Characters and Unicode

Total characters9986
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique549 ?
Unique (%)15.4%

Sample

1st row45
2nd row99
3rd row52
4th row59
5th row90
ValueCountFrequency (%)
32 61
 
1.7%
37 58
 
1.6%
52 58
 
1.6%
59 43
 
1.2%
60 42
 
1.2%
48 41
 
1.2%
19 41
 
1.2%
47 40
 
1.1%
41 40
 
1.1%
45 40
 
1.1%
Other values (894) 3092
87.0%
2024-11-22T18:48:36.535297image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1847
18.5%
2 1135
11.4%
3 1056
10.6%
4 900
9.0%
5 866
8.7%
8 741
7.4%
. 710
 
7.1%
6 707
 
7.1%
7 684
 
6.8%
9 652
 
6.5%
Other values (2) 688
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9199
92.1%
Other Punctuation 787
 
7.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1847
20.1%
2 1135
12.3%
3 1056
11.5%
4 900
9.8%
5 866
9.4%
8 741
8.1%
6 707
 
7.7%
7 684
 
7.4%
9 652
 
7.1%
0 611
 
6.6%
Other Punctuation
ValueCountFrequency (%)
. 710
90.2%
, 77
 
9.8%

Most occurring scripts

ValueCountFrequency (%)
Common 9986
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1847
18.5%
2 1135
11.4%
3 1056
10.6%
4 900
9.0%
5 866
8.7%
8 741
7.4%
. 710
 
7.1%
6 707
 
7.1%
7 684
 
6.8%
9 652
 
6.5%
Other values (2) 688
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9986
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1847
18.5%
2 1135
11.4%
3 1056
10.6%
4 900
9.0%
5 866
8.7%
8 741
7.4%
. 710
 
7.1%
6 707
 
7.1%
7 684
 
6.8%
9 652
 
6.5%
Other values (2) 688
 
6.9%
Distinct2929
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2024-11-22T18:48:36.982961image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.0163105
Min length5

Characters and Unicode

Total characters21394
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2549 ?
Unique (%)71.7%

Sample

1st row18,889
2nd row23,414
3rd row23,654
4th row18,983
5th row19,595
ValueCountFrequency (%)
20,000 22
 
0.6%
25,000 20
 
0.6%
50,000 10
 
0.3%
30,000 10
 
0.3%
26,667 9
 
0.3%
15,000 9
 
0.3%
24,000 8
 
0.2%
16,667 8
 
0.2%
40,000 7
 
0.2%
27,500 7
 
0.2%
Other values (2919) 3446
96.9%
2024-11-22T18:48:37.530680image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 3557
16.6%
2 2643
12.4%
1 2184
10.2%
3 2110
9.9%
0 2013
9.4%
5 1663
7.8%
4 1641
7.7%
6 1502
7.0%
7 1426
6.7%
8 1388
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17837
83.4%
Other Punctuation 3557
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2643
14.8%
1 2184
12.2%
3 2110
11.8%
0 2013
11.3%
5 1663
9.3%
4 1641
9.2%
6 1502
8.4%
7 1426
8.0%
8 1388
7.8%
9 1267
7.1%
Other Punctuation
ValueCountFrequency (%)
, 3557
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21394
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 3557
16.6%
2 2643
12.4%
1 2184
10.2%
3 2110
9.9%
0 2013
9.4%
5 1663
7.8%
4 1641
7.7%
6 1502
7.0%
7 1426
6.7%
8 1388
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21394
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 3557
16.6%
2 2643
12.4%
1 2184
10.2%
3 2110
9.9%
0 2013
9.4%
5 1663
7.8%
4 1641
7.7%
6 1502
7.0%
7 1426
6.7%
8 1388
 
6.5%

Tenure
Text

Distinct116
Distinct (%)3.3%
Missing1
Missing (%)< 0.1%
Memory size27.9 KiB
2024-11-22T18:48:37.883244image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length35
Median length34
Mean length22.782278
Min length8

Characters and Unicode

Total characters80991
Distinct characters27
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)0.8%

Sample

1st row99 yrs lease commencing from 1997
2nd row99 yrs lease commencing from 2011
3rd row99 yrs lease commencing from 2014
4th row99 yrs lease commencing from 1997
5th row99 yrs lease commencing from 1970
ValueCountFrequency (%)
from 2085
14.9%
yrs 2085
14.9%
lease 2085
14.9%
commencing 2085
14.9%
99 1624
11.6%
freehold 1470
10.5%
999 390
 
2.8%
2011 188
 
1.3%
1989 148
 
1.1%
1970 141
 
1.0%
Other values (97) 1679
12.0%
2024-11-22T18:48:38.222470image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10425
12.9%
e 9195
11.4%
m 6255
 
7.7%
9 6142
 
7.6%
o 5640
 
7.0%
r 5640
 
7.0%
s 4170
 
5.1%
c 4170
 
5.1%
n 4170
 
5.1%
l 3555
 
4.4%
Other values (17) 21629
26.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 56160
69.3%
Decimal Number 12936
 
16.0%
Space Separator 10425
 
12.9%
Uppercase Letter 1470
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 9195
16.4%
m 6255
11.1%
o 5640
10.0%
r 5640
10.0%
s 4170
7.4%
c 4170
7.4%
n 4170
7.4%
l 3555
 
6.3%
g 2085
 
3.7%
f 2085
 
3.7%
Other values (5) 9195
16.4%
Decimal Number
ValueCountFrequency (%)
9 6142
47.5%
1 2234
 
17.3%
0 1128
 
8.7%
2 962
 
7.4%
8 951
 
7.4%
7 580
 
4.5%
6 330
 
2.6%
3 256
 
2.0%
4 210
 
1.6%
5 143
 
1.1%
Space Separator
ValueCountFrequency (%)
10425
100.0%
Uppercase Letter
ValueCountFrequency (%)
F 1470
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 57630
71.2%
Common 23361
28.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 9195
16.0%
m 6255
10.9%
o 5640
9.8%
r 5640
9.8%
s 4170
 
7.2%
c 4170
 
7.2%
n 4170
 
7.2%
l 3555
 
6.2%
g 2085
 
3.6%
f 2085
 
3.6%
Other values (6) 10665
18.5%
Common
ValueCountFrequency (%)
10425
44.6%
9 6142
26.3%
1 2234
 
9.6%
0 1128
 
4.8%
2 962
 
4.1%
8 951
 
4.1%
7 580
 
2.5%
6 330
 
1.4%
3 256
 
1.1%
4 210
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80991
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10425
12.9%
e 9195
11.4%
m 6255
 
7.7%
9 6142
 
7.6%
o 5640
 
7.0%
r 5640
 
7.0%
s 4170
 
5.1%
c 4170
 
5.1%
n 4170
 
5.1%
l 3555
 
4.4%
Other values (17) 21629
26.7%

Postal District
Real number (ℝ)

High correlation 

Distinct25
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.1768841
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.9 KiB
2024-11-22T18:48:38.277609image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median8
Q314
95-th percentile21
Maximum27
Range26
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.5722799
Coefficient of variation (CV)0.71617772
Kurtosis-0.28155378
Mean9.1768841
Median Absolute Deviation (MAD)6
Skewness0.62388268
Sum32633
Variance43.194864
MonotonicityNot monotonic
2024-11-22T18:48:38.319772image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 624
17.5%
7 438
12.3%
8 432
12.1%
14 382
10.7%
9 241
 
6.8%
15 233
 
6.6%
2 214
 
6.0%
6 164
 
4.6%
12 116
 
3.3%
21 110
 
3.1%
Other values (15) 602
16.9%
ValueCountFrequency (%)
1 624
17.5%
2 214
 
6.0%
3 99
 
2.8%
4 5
 
0.1%
5 37
 
1.0%
6 164
 
4.6%
7 438
12.3%
8 432
12.1%
9 241
 
6.8%
10 47
 
1.3%
ValueCountFrequency (%)
27 24
 
0.7%
26 7
 
0.2%
25 90
2.5%
23 11
 
0.3%
22 45
1.3%
21 110
3.1%
20 34
 
1.0%
19 106
3.0%
18 10
 
0.3%
16 37
 
1.0%

District Name
Categorical

High correlation 

Distinct25
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
Raffles Place, Cecil, Marina, People's Park
624 
Middle Road, Golden Mile
438 
Little India
432 
Geylang, Eunos
382 
Orchard, Cairnhill, River Valley
241 
Other values (20)
1439 

Length

Max length52
Median length44
Mean length28.142295
Min length7

Characters and Unicode

Total characters100074
Distinct characters52
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row Middle Road, Golden Mile
2nd row Geylang, Eunos
3rd row Kranji, Woodgrove
4th row Middle Road, Golden Mile
5th row Anson, Tanjong Pagar

Common Values

ValueCountFrequency (%)
Raffles Place, Cecil, Marina, People's Park 624
17.5%
Middle Road, Golden Mile 438
12.3%
Little India 432
12.1%
Geylang, Eunos 382
10.7%
Orchard, Cairnhill, River Valley 241
 
6.8%
Katong, Joo Chiat, Amber Road 233
 
6.6%
Anson, Tanjong Pagar 214
 
6.0%
High Street, Beach Road (part) 164
 
4.6%
Balestier, Toa Payoh, Serangoon 116
 
3.3%
Upper Bukit Timah, Clementi Park, Ulu Pandan 110
 
3.1%
Other values (15) 602
16.9%

Length

2024-11-22T18:48:38.361804image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
road 882
 
6.2%
park 734
 
5.2%
raffles 624
 
4.4%
people's 624
 
4.4%
place 624
 
4.4%
marina 624
 
4.4%
cecil 624
 
4.4%
middle 438
 
3.1%
golden 438
 
3.1%
mile 438
 
3.1%
Other values (77) 8170
57.5%

Most occurring characters

ValueCountFrequency (%)
14220
14.2%
a 9101
 
9.1%
e 8202
 
8.2%
l 6297
 
6.3%
n 5795
 
5.8%
o 5415
 
5.4%
, 5385
 
5.4%
i 5168
 
5.2%
r 4328
 
4.3%
d 3430
 
3.4%
Other values (42) 32733
32.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 65461
65.4%
Space Separator 14220
 
14.2%
Uppercase Letter 14056
 
14.0%
Other Punctuation 6009
 
6.0%
Close Punctuation 164
 
0.2%
Open Punctuation 164
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 2623
18.7%
R 1757
12.5%
M 1559
11.1%
C 1304
9.3%
G 963
 
6.9%
T 717
 
5.1%
B 648
 
4.6%
A 528
 
3.8%
E 481
 
3.4%
L 469
 
3.3%
Other values (14) 3007
21.4%
Lowercase Letter
ValueCountFrequency (%)
a 9101
13.9%
e 8202
12.5%
l 6297
9.6%
n 5795
8.9%
o 5415
8.3%
i 5168
7.9%
r 4328
 
6.6%
d 3430
 
5.2%
t 2568
 
3.9%
s 2377
 
3.6%
Other values (13) 12780
19.5%
Other Punctuation
ValueCountFrequency (%)
, 5385
89.6%
' 624
 
10.4%
Space Separator
ValueCountFrequency (%)
14220
100.0%
Close Punctuation
ValueCountFrequency (%)
) 164
100.0%
Open Punctuation
ValueCountFrequency (%)
( 164
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 79517
79.5%
Common 20557
 
20.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 9101
 
11.4%
e 8202
 
10.3%
l 6297
 
7.9%
n 5795
 
7.3%
o 5415
 
6.8%
i 5168
 
6.5%
r 4328
 
5.4%
d 3430
 
4.3%
P 2623
 
3.3%
t 2568
 
3.2%
Other values (37) 26590
33.4%
Common
ValueCountFrequency (%)
14220
69.2%
, 5385
 
26.2%
' 624
 
3.0%
) 164
 
0.8%
( 164
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 100074
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14220
14.2%
a 9101
 
9.1%
e 8202
 
8.2%
l 6297
 
6.3%
n 5795
 
5.8%
o 5415
 
5.4%
, 5385
 
5.4%
i 5168
 
5.2%
r 4328
 
4.3%
d 3430
 
3.4%
Other values (42) 32733
32.7%

Floor Level
Categorical

High correlation 

Distinct11
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
01 to 05
1530 
-
893 
06 to 10
473 
11 to 15
256 
16 to 20
 
133
Other values (6)
271 

Length

Max length8
Median length8
Mean length6.242126
Min length1

Characters and Unicode

Total characters22197
Distinct characters12
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row01 to 05
2nd row01 to 05
3rd row06 to 10
4th row06 to 10
5th row16 to 20

Common Values

ValueCountFrequency (%)
01 to 05 1530
43.0%
- 893
25.1%
06 to 10 473
 
13.3%
11 to 15 256
 
7.2%
16 to 20 133
 
3.7%
B1 to B5 123
 
3.5%
21 to 25 87
 
2.4%
26 to 30 29
 
0.8%
36 to 40 15
 
0.4%
31 to 35 14
 
0.4%

Length

2024-11-22T18:48:38.405334image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
to 2663
30.0%
01 1530
17.2%
05 1530
17.2%
893
 
10.1%
06 473
 
5.3%
10 473
 
5.3%
11 256
 
2.9%
15 256
 
2.9%
16 133
 
1.5%
20 133
 
1.5%
Other values (12) 542
 
6.1%

Most occurring characters

ValueCountFrequency (%)
5326
24.0%
0 4183
18.8%
1 3131
14.1%
t 2663
12.0%
o 2663
12.0%
5 2013
 
9.1%
- 893
 
4.0%
6 650
 
2.9%
2 336
 
1.5%
B 246
 
1.1%
Other values (2) 93
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10406
46.9%
Space Separator 5326
24.0%
Lowercase Letter 5326
24.0%
Dash Punctuation 893
 
4.0%
Uppercase Letter 246
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4183
40.2%
1 3131
30.1%
5 2013
19.3%
6 650
 
6.2%
2 336
 
3.2%
3 72
 
0.7%
4 21
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
t 2663
50.0%
o 2663
50.0%
Space Separator
ValueCountFrequency (%)
5326
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 893
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 246
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16625
74.9%
Latin 5572
 
25.1%

Most frequent character per script

Common
ValueCountFrequency (%)
5326
32.0%
0 4183
25.2%
1 3131
18.8%
5 2013
 
12.1%
- 893
 
5.4%
6 650
 
3.9%
2 336
 
2.0%
3 72
 
0.4%
4 21
 
0.1%
Latin
ValueCountFrequency (%)
t 2663
47.8%
o 2663
47.8%
B 246
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22197
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5326
24.0%
0 4183
18.8%
1 3131
14.1%
t 2663
12.0%
o 2663
12.0%
5 2013
 
9.1%
- 893
 
4.0%
6 650
 
2.9%
2 336
 
1.5%
B 246
 
1.1%
Other values (2) 93
 
0.4%

Interactions

2024-11-22T18:48:28.598835image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2024-11-22T18:48:38.434019image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
District NameFloor LevelPostal DistrictProperty TypeType of Area
District Name1.0000.2350.9980.4220.432
Floor Level0.2351.0000.1900.7850.925
Postal District0.9980.1901.0000.3080.276
Property Type0.4220.7850.3081.0000.948
Type of Area0.4320.9250.2760.9481.000

Missing values

2024-11-22T18:48:28.656900image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-11-22T18:48:28.735055image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Project NameStreet NameProperty TypeTransacted Price ($)Area (SQFT)Unit Price ($ PSF)Sale DateType of AreaArea (SQM)Unit Price ($ PSM)TenurePostal DistrictDistrict NameFloor Level
0SUNSHINE PLAZABENCOOLEN STREETOffice850,000484.381,755Oct-24Strata4518,88999 yrs lease commencing from 19977Middle Road, Golden Mile01 to 05
1PAYA LEBAR SQUAREPAYA LEBAR ROADOffice2,318,0001,065.642,175Oct-24Strata9923,41499 yrs lease commencing from 201114Geylang, Eunos01 to 05
2WOODS SQUAREWOODLANDS SQUAREOffice1,230,000559.732,197Oct-24Strata5223,65499 yrs lease commencing from 201425Kranji, Woodgrove06 to 10
3SUNSHINE PLAZABENCOOLEN STREETOffice1,120,000635.081,764Oct-24Strata5918,98399 yrs lease commencing from 19977Middle Road, Golden Mile06 to 10
4INTERNATIONAL PLAZAANSON ROADOffice1,763,580968.761,820Oct-24Strata9019,59599 yrs lease commencing from 19702Anson, Tanjong Pagar16 to 20
5SUNSHINE PLAZABENCOOLEN STREETOffice1,150,000667.371,723Oct-24Strata6218,54899 yrs lease commencing from 19977Middle Road, Golden Mile01 to 05
6111 SOMERSETSOMERSET ROADOffice2,200,000785.772,800Oct-24Strata7330,13799 yrs lease commencing from 19759Orchard, Cairnhill, River Valley11 to 15
7SOUTHBANKNORTH BRIDGE ROADOffice1,688,8881,011.821,669Oct-24Strata9417,96799 yrs lease commencing from 20067Middle Road, Golden Mile16 to 20
8INTERNATIONAL PLAZAANSON ROADOffice3,500,0002,357.321,485Oct-24Strata21915,98299 yrs lease commencing from 19702Anson, Tanjong Pagar11 to 15
9SUNSHINE PLAZABENCOOLEN STREETOffice1,280,000731.951,749Oct-24Strata6818,82499 yrs lease commencing from 19977Middle Road, Golden Mile01 to 05
Project NameStreet NameProperty TypeTransacted Price ($)Area (SQFT)Unit Price ($ PSF)Sale DateType of AreaArea (SQM)Unit Price ($ PSM)TenurePostal DistrictDistrict NameFloor Level
3546N.A.HONGKONG STREETShop House7,100,0001,669.504,253Nov-19Land155.145,77799 yrs lease commencing from 19511Raffles Place, Cecil, Marina, People's Park-
3547N.A.JOO CHIAT ROADShop House23,200,00010,469.072,216Nov-19Land972.623,854Freehold15Katong, Joo Chiat, Amber Road-
3548N.A.JALAN BESARShop House5,300,0001,473.593,597Nov-19Land136.938,714Freehold8Little India-
3549LITTLE INDIA CONSERVATION AREANORRIS ROADShop House2,950,000982.753,002Nov-19Land91.332,311Freehold8Little India-
3550LITTLE INDIA CONSERVATION AREADICKSON ROADShop House3,000,0001,416.542,118Nov-19Land131.622,79699 yrs lease commencing from 19308Little India-
3551N.A.JOO CHIAT PLACEShop House8,000,0003,565.042,244Nov-19Land331.224,155Freehold15Katong, Joo Chiat, Amber Road-
3552N.A.OUTRAM ROADShop House5,180,0001,528.493,389Oct-19Land14236,479Freehold3Queenstown, Tiong Bahru-
3553KRETA AYER CONSERVATION AREAPAGODA STREETShop House16,250,0001,309.9812,405Oct-19Land121.7133,525Freehold1Raffles Place, Cecil, Marina, People's Park-
3554KRETA AYER CONSERVATION AREASMITH STREETShop House7,000,0001,076.406,503Oct-19Land10070,000999 yrs lease commencing from 18751Raffles Place, Cecil, Marina, People's Park-
3555N.A.KILLINEY ROADShop House6,050,0001,133.455,338Oct-19Land105.357,455Freehold9Orchard, Cairnhill, River Valley-

Duplicate rows

Most frequently occurring

Project NameStreet NameProperty TypeTransacted Price ($)Area (SQFT)Unit Price ($ PSF)Sale DateType of AreaArea (SQM)Unit Price ($ PSM)TenurePostal DistrictDistrict NameFloor Level# duplicates
5CENTRIUM SQUARESERANGOON ROADOffice1,631,450613.552,659Nov-20Strata5728,622Freehold8Little India11 to 154
12HIGH STREET CENTRENORTH BRIDGE ROADRetail376,700376.741,000Mar-24Strata3510,76399 yrs lease commencing from 19696High Street, Beach Road (part)01 to 053
28ROYAL SQUARE AT NOVENAIRRAWADDY ROADRetail2,694,174538.25,006Aug-23Strata5053,88399 yrs lease commencing from 201312Balestier, Toa Payoh, Serangoon01 to 053
34THE GOLDEN LANDMARKVICTORIA STREETRetail660,000290.632,271Dec-22Strata2724,44499 yrs lease commencing from 19817Middle Road, Golden Mile01 to 053
39WOODS SQUAREWOODLANDS SQUAREOffice1,045,352559.731,868Dec-20Strata5220,10399 yrs lease commencing from 201425Kranji, Woodgrove06 to 103
01953TESSENSOHN ROADRetail1,560,000516.673,019Oct-20Strata4832,500Freehold8Little India01 to 052
128 RC SUITESRACE COURSE LANERetail1,680,000430.563,902May-24Strata4042,000Freehold8Little India01 to 052
2CENTRIUM SQUARESERANGOON ROADOffice1,523,900570.492,671Dec-19Strata5328,753Freehold8Little India11 to 152
3CENTRIUM SQUARESERANGOON ROADOffice1,560,000613.552,543Dec-19Strata5727,368Freehold8Little India11 to 152
4CENTRIUM SQUARESERANGOON ROADOffice1,567,800570.492,748Nov-20Strata5329,581Freehold8Little India16 to 202